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Research Data Management


This guide is intended to support the NUS community in effective research data management throughout the data lifecycle of data planning, documenting, storage, sharing, and long-term preservation. This guide is collaboratively developed by NUS, NTU and SMU Libraries.

What is Research Data Management

Research Data Management (RDM) is "how you look after your data throughout your project. It covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your data and ensures that research data are managed according to legal, statutory, ethical and funding body requirements" (Whyte, A. & Tedds, J., 2011).

RDM occurs in every stage of the research lifecycle, not just at the end where all the data files are simply zipped up in a folder for storage.

Source: University of California Santa Cruz, Research Data Management LibGuide

What is Research Data

It is universally acknowledged that researchers are interested in data of all kinds, regardless of origin or type.

Here are some of the recognised definitions of research data:

"Research data, unlike other types of information, is collected, observed, or created, for purposes of analysis to produce original research results." Edinburgh University Data Library Research Data Management Handbook  

“Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media”. The Queensland University of Technology Management of Research Data Policy

“The recorded information (regardless of the form or the media in which they may exist) necessary to support or validate a research project’s observations, findings or outputs”. The University of Oxford Policy on Management of Research Data and Records

In addition to research data, research data management also covers managing of research records both during and beyond the life of a project. Examples of such research records include:

  • Correspondence (electronic mail and paper-based correspondence)
  • Project files
  • Grant applications
  • Ethics applications
  • Technical reports
  • Research reports
  • Signed consent forms

Source: MANTRA

Why Manage Research Data

Research data represents significant value to researchers and the University, and good stewardship of research data is necessary to validate the outcomes and maintain the integrity of research results.

Ensuring research integrity and reproducibility

Increasing your research efficiency

Ensuring research data and records are accurate, complete, authentic and reliable

Saving time and resources in the long run

Enhancing data security and minimising the risk of data loss

Preventing duplication of effort by enabling others to use your data

Complying with practices conducted in industry and commerce

Facilitating the analysis of change, by providing data with which data at other points in time can be compared

Meeting funding body grant requirements (if applicable)

Source: MANTRA